Nearly every mid-sized or large organization is embracing AI as a productivity enhancer, but how many are truly weighing the cybersecurity and risk management implications?
A recent Harvard Business School study revealed that business tasks were completed 25% faster with AI, underscoring the technology’s role as a catalyst for operational efficiency and innovation. It’s easy to see why, with AI delivering a host of measurable benefits, including:
- Elevated Sales Analytics: AI can analyze sales data in real-time, providing insights that lead to more impactful sales strategies and higher revenue
- Tailored Customer Support: AI-driven chatbots can offer 24/7 support with user-driven answers, significantly improving customer satisfaction
- Automating Routine Tasks: Because AI can effectively perform manual tasks via automation, employees can take the time to focus on more strategic activities.
- Optimizing Operations: AI enables organizations to fully optimize operations across the board, leading to enhanced performance across various levels of the organization.
However, while generative AI is often sold as a productivity enhancer, tools such as ChatGPT, Gemini, Perplexity, Otter and more can introduce real organizational cybersecurity risks. These solutions can compromise the confidentiality of corporate intellectual property through data leakage, expose your organization to legal action if AI “borrows” from existing code without a license and more.
Employees can also use AI tools on an organization’s network without knowledge of security or IT. These unmonitored applications, known as “shadow AI,” are one of the top causes of data breaches today, which can cost an average of.
AI is also not always correct, and yet many employees regard its outputs as the concrete truth. Unfortunately, this can also get organizations in trouble. For example, a was the subject of a lawsuit because he presented nonexistent citations generated by AI during a case. All the cases that the lawyer used to illustrate the impact of similar injuries on their client were made up.
CEOs, IT experts and other visionary IT leaders all agree: The benefits of AI are too powerful to go unused or unchecked. To deploy AI successfully, organizations need a comprehensive AI policy.
Here are the top five factors to consider when developing and implementing an effective AI policy usage for your organization.
- Explain AI in Layman’s Terms: Technical employees may be familiar with AI, machine learning, automation and other related concepts, but other departments may not. The first step to a clear AI policy is ensuring that all employees have a shared understanding. Organizations must include a section that establishes a common language to facilitate informed discussions and policy adherence across the whole company.
- Consider Unique Risks: Whether it’s a financial organization using AI to analyze customers’ spending patterns or a healthcare facility using a chatbot to better diagnose a patient, each sector must consider what it must lose if AI is compromised or has underlying biases. The next section of the AI usage policy should identify each company’s unique risks, provide real-world examples and outline proactive strategies to mitigate them such as audits, bias detection protocols and other data protection measures.
- Set Clear Boundaries: To prevent AI misuse, organizations must set clear limits on AI applications to avoid legal, ethical and/or reputational harm. In this section of an AI usage policy, organizations might include bans on discriminatory AI practices, AI-generated content designed to mislead or deceive, or any unauthorized data collection. These set guidelines can help employees understand what is and is not permitted.
- Establish Accountability: Organizations have to add a section on the repercussions of failing to adhere to AI policies. Depending on the severity of the discretion, consequences could range from corrective training and internal reviews to termination in the case of more severe and intentional violations. By laying these out, organizations can reinforce the importance of responsible AI usage.
AI integration is both complex and exciting, offering organizations opportunities to enhance efficiency, automate processes and drive projects forward. However, incorporating AI into existing workflows requires careful planning, strategic alignment between business stakeholders and a clear framework to ensure responsible use. A well-defined AI usage policy can serve as the foundation for successful AI, helping organizations set the standard for ethical AI adoption, data security and compliance with existing and future industry regulations.
